Wearable apparatus and operating method thereof

Abstract

A wearable device is disclosed. One embodiment processes a state variable defined based on user movement information, determines an interaction mode of the wearable device based on a gain related to the strength of the torque of the wearable device, selects one of motion types belonging to the determined interaction mode based on the user's walking parameters, determines a control factor for the torque based on the selected motion type, and generates the torque based on the processed state variable, the gain, and the determined control factor.

Description

Technology Field

[0001] The following embodiments relate to wearable devices. Background Technology

[0002] With the recent intensification of the aging society, the number of people complaining of pain and discomfort due to joint problems is increasing, and interest in walking assistance devices that can facilitate walking for the elderly or patients with joint discomfort is growing. In addition, exercise assistance devices are being developed to strengthen the human body's muscles. means of solving the problem

[0003] A method of operation of a wearable device according to one side comprises: processing a defined state variable based on user movement information; determining an interaction mode of the wearable device based on a gain related to the strength of the torque of the wearable device; selecting one of motion types belonging to the determined interaction mode based on the user's walking parameters; determining a control factor for the torque based on the selected motion type; and generating the torque based on the processed state variable, the gain, and the determined control factor.

[0004] The step of processing the above state variable may include a step of smoothing the above state variable.

[0005] The step of determining the interaction mode may include selecting a first interaction mode that assists the user's movement when the gain is greater than or equal to a reference value and is positive, selecting a second interaction mode that resists the user's movement when the gain is greater than or equal to the reference value and is negative, and selecting a third interaction mode that provides high resistance to the user's movement when the gain is less than the reference value.

[0006] The step of selecting one of the above motion types may include: determining the motion type of the wearable device as a walk motion type when the first walking characteristic value within the walking parameter is less than or equal to a first threshold value; determining the motion type as a walk-to-run motion type when the first walking characteristic value is greater than the first threshold value and less than or equal to a second threshold value; and determining the motion type as a run motion type when the first walking characteristic value is greater than the second threshold value.

[0007] The above first walking characteristic value may include the user's cadence.

[0008] The step of selecting one of the above motion types may include: determining the motion type of the wearable device as a high-resistance motion type when the second walking characteristic value within the walking parameter is greater than the third threshold value; and determining the motion type as a slow motion type when the second walking characteristic value is less than the fourth threshold value.

[0009] The above second gait characteristic value may include the average of the lengths of each of the two hip joint angle curves over a predetermined time.

[0010] The above determining step may include a step of adjusting at least one of a smoothing factor used to smooth the signal sensing the user's movement and a delay related to the output timing of the torque when a motion type change event occurs by selecting one of the above motion types.

[0011] The above adjusting step may include the step of decreasing the smoothing factor and increasing the delay when a motion type change event occurs as a work type is selected among the motion types.

[0012] The above adjusting step may include increasing the smoothing factor and decreasing the delay when a motion type change event occurs by selecting a run type among the motion types.

[0013] The step of generating the torque may include applying the gain, the determined control factor, and the compensation factor to the processed state variable; and generating the torque according to the result of the application.

[0014] The above movement information may include the angles of both hip joints of the user.

[0015] A wearable device according to one side comprises: a controller that processes a state variable defined based on user movement information, determines an interaction mode of the wearable device based on a gain related to the strength of the torque of the wearable device, selects one of motion types belonging to the determined interaction mode based on the user's walking parameters, determines a control factor for the torque based on the selected motion type, and controls an actuator based on the processed state variable, the gain, and the determined control factor; and an actuator that generates torque according to the control of the controller.

[0016] The above controller can smooth the state variable.

[0017] The controller may select a first interaction mode that assists the user's movement when the gain is greater than or equal to a reference value and is positive, select a second interaction mode that resists the user's movement when the gain is greater than or equal to a reference value and is negative, and select a third interaction mode that resists the user's movement when the gain is less than the reference value.

[0018] The controller may determine the motion type of the wearable device as a walk motion type when the first walking characteristic value within the walking parameter is less than or equal to a first threshold value, determine the motion type as a walk-to-run motion type when the first walking characteristic value is greater than the first threshold value and less than or equal to a second threshold value, and determine the motion type as a run motion type when the first walking characteristic value is greater than the second threshold value.

[0019] The above first walking characteristic value may include the user's cadence.

[0020] The controller can determine the motion type of the wearable device as a high-resistance motion type when the second walking characteristic value within the walking parameter is greater than the third threshold value, and determine the motion type as a slow motion type when the second walking characteristic value is less than the fourth threshold value.

[0021] The above second gait characteristic value may include the average of the lengths of each of the two hip joint angle curves over a predetermined time.

[0022] The above controller can adjust at least one of a smoothing factor used to smooth the signal sensing the user's movement and a delay related to the output timing of the torque when a motion type change event occurs by selecting one of the above motion types.

[0023] When a motion type change event occurs as a work type is selected among the motion types, the controller may decrease the smoothing factor and increase the delay.

[0024] When a motion type change event occurs as a run type is selected among the motion types, the controller can increase the smoothing factor and decrease the delay.

[0025] The controller can apply the gain, the determined control factor, and the compensation factor to the processed state variable.

[0026] The above movement information may include the angles of both hip joints of the user. Brief explanation of the drawing

[0027] FIGS. 1 to 3 are drawings for explaining a wearable device according to one embodiment. FIGS. 4 to 7 are drawings for explaining the operation of a wearable device according to one embodiment. FIG. 8 is a drawing for explaining a second walking characteristic value according to one embodiment. FIG. 9 is a drawing for explaining an example of a state machine of a wearable device according to one embodiment. FIG. 10 is a flowchart for explaining the operation method of a wearable device according to one embodiment. FIG. 11 is a block diagram illustrating a wearable device according to one embodiment. Specific details for implementing the invention

[0028] Hereinafter, embodiments will be described in detail with reference to the attached drawings.

[0029] Various modifications may be made to the embodiments described below. The embodiments described below are not intended to limit the forms of practice and should be understood to include all modifications, equivalents, and substitutions thereof.

[0030] The terms used in the embodiments are used merely to describe specific embodiments and are not intended to limit the embodiments. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to indicate the presence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0031] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments pertain. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0032] In addition, when describing with reference to the attached drawings, identical components are assigned the same reference numeral regardless of drawing symbols, and redundant descriptions thereof are omitted. When describing the embodiments, if it is determined that a detailed description of related prior art could unnecessarily obscure the essence of the embodiments, such detailed description is omitted.

[0034] FIGS. 1 to 3 are drawings for explaining a wearable device according to one embodiment.

[0035] Referring to FIG. 1, the wearable device (110) senses or acquires movement information of the user (120) and generates torque based on said movement information and various factors. For example, the wearable device (110) can generate an assisting torque to assist the walking of the user (120). As another example, the wearable device (110) can generate a resistance torque to provide resistance to the walking of the user (120). The torque generation of the wearable device (110) will be described later through FIG. 4.

[0036] The wearable device (110) may be a hip type worn on the hip joint or thigh of the user (120), an ankle type worn on the ankle of the user (120), or a knee type worn on the knee of the user (120), but is not limited thereto. An example of a hip-type wearable device (110) is illustrated in FIGS. 2 and FIGS. 3.

[0037] In the example illustrated in FIGS. 2 and 3, the actuators (210-1 and 210-2) of the wearable device (110) may be located near the hip joint of the user (120), and the controller (310) of the wearable device (110) may be located near the waist. Alternatively, the hip-type wearable device (110) may be designed such that the actuators (210-1 and 210-2) are located near the hip joint of the user (120) and the controller (310) is located near the waist of the user (120). The locations of the actuators (210-1 and 210-2) and the controller (310) are not limited to the example illustrated in FIGS. 2 and 3.

[0039] FIGS. 4 to 7 are drawings for explaining the operation of a wearable device according to one embodiment.

[0040] Referring to FIG. 4, the wearable device (110) senses the movement of the user (120) using a sensor (410). In other words, the wearable device (110) obtains movement information of the user (120). The movement information may include, for example, the angles of both hip joints of the user (120). Referring to the example illustrated in FIG. 5, the wearable device (110) uses an encoder located near the actuator (210-1) to obtain the angle of the user's (120) left hip joint q l (t) The right hip joint angle of the user (120) can be sensed or acquired using an encoder located near the actuator (210-2). q r (t) It can be sensed or acquired. In the example illustrated in FIG. 5, the left leg moves forward. Left hip joint angle q l (t) can be less than 0, and the right hip joint angle q r (t) can be greater than 0. Depending on the implementation, in the example shown in FIG. 5, the left hip joint angle q l (t) It can be greater than 0 and the right hip joint angle q r (t) It can be less than 0.

[0041] Returning to FIG. 4, the wearable device (110) defines a state variable (420). For example, the wearable device (110) sin( q r ( t )) and sin( q l ( t State variable corresponding to the difference between )) y raw (t) It can define.

[0042] The wearable device (110) isy raw (t) Smoothing is performed on (430). By smoothing y raw (t) Noise can be removed from and y raw (t) The waveform can be smoothed out. For example, the wearable device (110) y raw (t) Low-pass filtering can be performed on it. Mathematical Equation 1 below shows an example of the smoothing result (or low-pass filtering result).

[0043]

[0044] In the above mathematical formula 1, y(t) represents the smoothing result, α represents the smoothing factor, and y ( t prv ) represents the previous smoothing result.

[0045] The smoothing result described through Equation 1 above is merely an example and is not limited to Equation 1 above. The smoothing result may vary depending on the type of smoothing technique (or low-pass filter).

[0046] The wearable device (110) provides movement information and gain k Based on this, the interaction mode and motion type of the wearable device (110) are determined (440). The motion information is, for example, the left hip joint angle. q l (t) and right hip joint angle q r (t) It may include gain kis a factor related to torque strength and can be a positive or negative number. Also, gain k It can be received from the user (120). For example, the user (120) may gain input on a user interface device (e.g., tablet PC, smartphone, etc.). k It can input, and the wearable device (110) gains from the corresponding user interface device k It can receive. Depending on the implementation, the user (120) can receive gain on the wearable device (110). k You can enter.

[0047] In one embodiment, the wearable device (110) is gain k One of several interaction modes can be determined based on this. The interaction modes may be distinguished or classified based on the type of torque (or force) that the wearable device (110) outputs to the user (120). The interaction modes include, for example, a first interaction mode that assists the movement of the user (120), a second interaction mode that provides resistance to the movement of the user (120), and a third interaction mode that provides high resistance to the movement of the user (120).

[0048] In one embodiment, the wearable device (110) may determine one of the motion types belonging to a determined interaction mode based on movement information. The motion types may be distinguished or classified based on the movement speed of the user (120). At this time, the motion types belonging to the first and second interaction modes may be different from the motion types belonging to the third interaction mode. The first and second interaction modes may include, for example, a walk motion type, a walk-to-run motion type, and a run motion type, and the third interaction mode may include, for example, a high resistance motion type and a slow motion type.

[0049] The determination of the interaction mode and motion type will be explained in detail with reference to Fig. 6.

[0050] Referring to FIG. 6, the wearable device (110) gain k a reference value r Determine whether there is an abnormality (610).

[0051] The wearable device (110) gains k a reference value r If it is above, gain k Determine whether the number is positive (620).

[0052] The wearable device (110) gains k If is positive, a first interaction mode is selected, and a motion type of the wearable device (110) is determined based on the first walking characteristic value (630). Here, the first walking characteristic value may include, for example, the cadence of the user (120). The cadence may be calculated based on the user's (120) step information (for example, the time taken and walking distance when the user (120) takes two steps).

[0053] For example, the wearable device (110) is a reference value r =-5 and gain kIf =+5, a first interaction mode can be selected. And, if the first walking characteristic value of the wearable device (110) is less than or equal to a first threshold value (e.g., 120, described later through FIG. 9), the motion type of the wearable device (110) can be determined as a walk motion type; if the first walking characteristic value is greater than the first threshold value and less than or equal to a second threshold value (e.g., 140, described later through FIG. 9), the motion type of the wearable device (110) can be determined as a walk-to-run motion type; and if the first walking characteristic value is greater than the second threshold value, the motion type of the wearable device (110) can be determined as a run motion type. In other words, the wearable device (110) can select a walk motion type by determining that the user (120) is walking if the user's (120) cadence is below a predetermined range, can select a walk-to-run motion type by determining that the user (120) is walking at a fast speed if the user's (120) cadence is within a predetermined range, and can select a run type by determining that the user (120) is running if the user's (120) cadence is above a predetermined range.

[0054] Gain k Since is positive, the wearable device (110) outputs a torque that assists the movement of the user (120) regardless of which motion type is selected in the first interaction mode. As will be described later, since the control factor is different for each motion type, the strength of the assisting torque increases as it goes from the walk motion type, to the walk-to-run motion type, and to the run motion type.

[0055] The wearable device (110) gains k If is negative, a second interaction mode is selected, and the motion type of the wearable device (110) is determined based on the first walking characteristic value (640). For example, a reference value r =-5 and gain kIf =-3, the wearable device (110) can select a second interaction mode. And, as described in step (630) above, the wearable device (110) can determine one of a walk motion type, a walk-to-run motion type, and a run motion type based on the first walking characteristic value. Gain k Since is negative, the wearable device (110) outputs a torque that resists the movement of the user (120) regardless of which motion type is selected in the second interaction mode. As will be described later, since the control factor is different for each motion type, the strength of the resistance torque increases as it goes from the walk motion type, to the walk-to-run motion type, and to the run motion type.

[0056] In step (610), the wearable device (110) gains k a reference value r If less than, a third interaction mode is selected, and the motion type of the wearable device (110) is determined based on the second walking characteristic value (650). For example, a reference value r =-5 and gain kIf = -7, the wearable device (110) can select a third interaction mode. And, if the second walking characteristic value is greater than the third threshold value (e.g., 0.5, which will be described later through FIG. 9), the wearable device (110) can determine the motion type of the wearable device (110) as a high-resistance motion type, and if the second walking characteristic value is less than the fourth threshold value (e.g., 0.4, which will be described later through FIG. 9), the wearable device (110) can determine the motion type of the wearable device (110) as a slow-motion type. In other words, the wearable device (110) can select a high-resistance motion type to apply high resistance to the movement of the user (120) if the second walking characteristic value of the user (120) is greater than the third threshold value, and can select a slow-motion type to apply a small amount of auxiliary torque to the walking of the user (120) if the second walking characteristic value of the user (120) is less than the fourth threshold value.

[0057] The second walking characteristic value may represent a value that can estimate the walking characteristics (e.g., walking speed) of the user (120) for a predetermined period of time. The second walking characteristic value will be described later through FIG. 8.

[0058] Returning to FIG. 4, the wearable device (110) determines a control factor (450) based on the determined motion type. The control factor is, for example, the smoothing factor described above. α and delay related to the output timing of torque Δt It may include at least one of the following. As will be described later, the control factor can affect the response characteristics of the torque and may be expressed differently as a response variable (or sensing response variable). The determination of the control factor will be explained with reference to FIG. 7.

[0059] Referring to FIG. 7, the wearable device (110) checks whether a motion type change event has occurred (710). For example, the wearable device (110) can check whether the motion type determined in step (440) is the same as the previous motion type. If the motion type determined in step (440) is not the same as the previous motion type, a change event occurs, and if the motion type determined in step (440) is the same as the previous motion type, a change event does not occur.

[0060] The wearable device (110) adjusts the control factor (720) when a motion type change event occurs. For example, the previous motion type may be a run motion type and a walk motion type may be determined in step (440). In this case, since a motion type change event occurs, the wearable device (110) can change from a control factor that is already set (i.e., a control factor corresponding to the run motion type) to a control factor corresponding to the walk motion type. In the embodiment, each motion type and control factor can be mapped on a lookup table. The adjustment of the control factor according to the motion type change is explained in detail through FIG. 9.

[0061] The wearable device (110) maintains the control factor that is already set when no change event of the motion type occurs (730).

[0062] Returning to FIG. 4, the wearable device (110) has a compensation factor based on a determined motion type. k comp Schedules (460). Reward factor k comp is a factor for compensating the magnitude of the torque. Also, the compensation factor k comp It can compensate for or correct the linear responsiveness of torque generation for each motion type.

[0063] For example, when the run motion type is determined in step (440), the wearable device (110) has a compensation factor k comp can be determined as 1.2, and if the walk motion type is determined in step (440), the compensation factor k comp can be determined to be 1, and if a high resistance motion type is determined in step (440), the compensation factor k comp can be determined to be 0.8, and if the slow motion type is determined in step (440), the compensation factor k comp -5 / k It can be determined as follows. In the embodiment, each motion type and compensation factor can be mapped on a lookup table.

[0064] The wearable device (110) is a smoothing result y(t) , gain k , control factor, and compensation factor k comp Torque is generated based on (470). Equation 2 below shows an example of torque τ(t).

[0065]

[0066] For example, the wearable device (110) can generate auxiliary torque in each motion type of the first interaction mode. At this time, since the control factor is different for each motion type, the gain k Even if they are the same, the auxiliary torque in the walk-to-run motion type may be greater than the auxiliary torque in the walk motion type, and the auxiliary torque in the run motion type may be greater than the auxiliary torque in the walk-to-run motion type.

[0067] As another example, the wearable device (110) can generate resistance torque in each motion type of the second interaction mode. In this case, since the control factor is different for each motion type, the gain k Even if they are the same, the resistance torque in the walk-to-run motion type may be greater than the resistance torque in the walk motion type, and the resistance torque in the run motion type may be greater than the resistance torque in the walk-to-run motion type.

[0068] As another example, the wearable device (110) can generate high resistance torque in the high resistance motion type of the third interaction mode. Here, the high resistance torque is stronger than the resistance torque in the second interaction mode. Additionally, the wearable device (110) can generate an assist torque that assists the user (120)'s slow walking with a weak intensity in the slow type of the third interaction mode.

[0070] FIG. 8 is a drawing for explaining a second walking characteristic value according to one embodiment.

[0071] Referring to Fig. 8, the right hip joint angle q r (t) It becomes a city.

[0072] The second gait characteristic value may be a value capable of gauging the gait characteristics of the user (120) over a predetermined period of time. The second gait characteristic value may be calculated, for example, based on the length of each of the hip joint angle curves for the last 1 second. For example, in the example illustrated in FIG. 8, the wearable device (110) has a right hip joint angle q r (t) of t~t-1 The length of the curve (810) during q r_length It can be calculated according to the mathematical formula 3 below.

[0073]

[0074] In mathematical formula 3 above is points (t, q) and adjacent points (t prv , q prv )It indicates the distance between. The wearable device (110) can calculate, according to the above mathematical formula 3, the distance between point (820-1) and point (820-2), the distance between point (820-2) and point (820-3), the distance between point (820-3) and point (820-4), the distance between point (820-4) and point (820-5), the distance between point (820-5) and point (820-6), the distance between point (820-6) and point (820-7), the distance between point (820-7) and point (820-8), the distance between point (820-8) and point (820-9), and the distance between point (820-9) and point (820-10). The wearable device (110) subtracts 1 from the sum of the calculated distances. q r_length can calculate.

[0075] Although not shown in FIG. 8, the wearable device (110) has a left hip joint angle according to the above mathematical formula 3. q l (t) The length of the curve from t to t-1 q l_length can calculate.

[0076] The wearable device (110) is q r_length and q l_length The average of can be calculated and the corresponding average can be determined as the second walking feature value.

[0078] FIG. 9 is a drawing for explaining an example of a state machine of a wearable device according to one embodiment.

[0079] Referring to Fig. 9, the reference value r An example of a state machine when =-5 is illustrated.

[0080] The wearable device (110) gains k If the gain is -5 or higher, a first or second interaction mode can be selected. At this time, the wearable device (110) gain kIf is positive, the first interaction mode can be selected, and the gain k If is negative, a second interaction mode can be selected. The wearable device (110) gain k If is less than -5, a third interaction mode can be selected.

[0081] <게인 k 가 -5 more than that

[0082] When the user (120)'s cadence becomes 130 while the wearable device (110) is operating in the walk motion type (910), the wearable device (110) can change from the walk motion type (910) to the walk-to-run motion type (920). Since the motion type has changed, the wearable device (110) adjusts the control factor. In other words, since the walk-to-run motion type (920) is not the same as the previous motion type, the walk motion type (910), the wearable device (110) adjusts the control factor. For example, the wearable device (110) can increase the smoothing factor and decrease the delay. In the example illustrated in FIG. 9, the wearable device (110) can increase the smoothing factor to a value within the range of 0.05 to 0.10 and decrease the delay to a value within the range of 0.25 to 0.20 to 0.25. When the cadence of the user (120) is 120 or higher, a saturation phenomenon or torque attenuation phenomenon may occur in which the torque does not increase in proportion to the walking speed due to smoothing (or low-pass filtering). In the walk-to-run motion type (920), smoothing is performed with a controlled smoothing factor and torque is generated with a controlled delay so that the saturation phenomenon can be resolved and the amount of torque attenuation can be compensated.

[0083] In the walk-to-run motion type (920), the smoothing factor and delay may be fixed values ​​within each range. Not limited thereto, in the walk-to-run motion type (920), the smoothing factor and delay may be values ​​that match the user's (120) cadence within each range. For example, if the user's (120) cadence is 120, the smoothing factor may be 0.055 and the delay may be 0.205. If the cadence is 130, the smoothing factor may be 0.075 and the delay may be 0.225. If the cadence is 140, the smoothing factor may be 0.095 and the delay may be 0.245.

[0084] When the user (120)'s cadence becomes 150 while the wearable device (110) is operating in the walk motion type (910), the wearable device (110) can change from the walk motion type (910) to the run motion type (930). Since the motion type has changed, the wearable device (110) adjusts the control factor. For example, the wearable device (110) can increase the smoothing factor and decrease the delay. In the example illustrated in FIG. 9, the wearable device (110) can increase the smoothing factor from 0.05 to 0.1 and decrease the delay from 0.25 to a value within the range of 0.15 to 0.20. Additionally, the wearable device (110) can adjust the compensation factor from 1 to 1.2. If the cadence of the user (120) exceeds 140, torque attenuation may occur due to smoothing (or low-pass filtering). In the run motion type (930), smoothing is performed with a controlled smoothing factor, and torque can be generated with a controlled delay and a controlled compensation factor so that the amount of torque attenuation can be compensated.

[0085] When the user's (120) cadence becomes 110 while the wearable device (110) is operating in a walk-to-run motion type (920), the wearable device (110) can change from the walk-to-run motion type (920) to a walk motion type (910). Since the motion type has changed, the wearable device (110) adjusts the control factor. For example, the wearable device (110) can decrease the smoothing factor and increase the delay. In the example illustrated in FIG. 9, the wearable device (110) can decrease the smoothing factor to 0.05 and increase the delay to 0.25.

[0086] When the user (120)'s cadence becomes 150 while the wearable device (110) is operating in a walk-to-run motion type (920), the wearable device (110) can change from the walk-to-run motion type (920) to a run motion type (930). Since the motion type has changed, the wearable device (110) adjusts the control factors. For example, the wearable device (110) can increase the smoothing factor and decrease the delay. Additionally, the wearable device (110) can increase the compensation factor. As described above, if the user (120)'s cadence exceeds 140, a torque damping phenomenon may occur. To prevent a torque damping phenomenon from occurring when changing from the walk-to-run motion type (920) to the run motion type (930), the wearable device (110) can perform smoothing with the adjusted smoothing factor and generate torque with the adjusted delay and the adjusted compensation factor.

[0087] When the user (120)'s cadence becomes 110 while the wearable device (110) is operating in a run motion type (930), the wearable device (110) can change from the run motion type (930) to a walk motion type (910). Since the motion type has changed, the wearable device (110) adjusts the control factor. For example, the wearable device (110) can decrease the smoothing factor and increase the delay. Additionally, the wearable device (110) can adjust the compensation factor from 1.2 to 1.

[0088] As described above, the control factors for each of the motion types (910 to 930) are different. In other words, at the same gain, the smoothing factor increases and the delay decreases as one moves from the walk motion type (910), the walk-to-run motion type (920), and the run motion type (930). By adjusting these control factors, the torque intensity can increase linearly and stably as the movement speed of the user (120) increases. Additionally, when the gain increases linearly, the torque intensity can increase linearly and stably. Accordingly, the linear response characteristics and control stability of the wearable device (110) can be improved.

[0089] <게인 k 가 -5 less than if>

[0090] While the wearable device (110) is operating in a high-resistance motion type (940) q length If α is less than 0.4, the wearable device (110) can be changed from a high-resistance motion type (940) to a slow-motion type (950). In other words, while the wearable device (110) is operating in the high-resistance motion type (940) q length If is less than 0.5 and greater than 0.4, the wearable device (110) can maintain a high resistance motion type (940). q length If α is less than 0.4, the wearable device (110) can be changed from a high-resistance motion type (940) to a slow-motion type (950). In the example illustrated in FIG. 9, the smoothing factor and delay are not changed when changing from a high-resistance motion type (940) to a slow-motion type (950). Likewise, the smoothing factor and delay are not changed when changing from a slow-motion type (950) to a high-resistance motion type (940). This is merely an example, and if there is a change in the motion type, it can be implemented so that at least one of the smoothing factor and delay is changed.

[0091] In the high resistance motion type (940), as the speed of the user's (120) movement increases, the torque intensity can also increase linearly and stably. Additionally, when the gain increases linearly, the torque intensity can also increase linearly and stably. Accordingly, the linear response characteristics and control stability of the wearable device (110) in the high resistance motion type (940) can be improved.

[0093] FIG. 10 is a flowchart for explaining the operation method of a wearable device according to one embodiment.

[0094] Referring to FIG. 10, the wearable device (110) processes a defined state variable based on the movement information of the user (120) (1010). For example, the wearable device (110) processes the above-described state variable y raw (t) It can be smoothed.

[0095] The wearable device (110) determines the interaction mode of the wearable device (110) based on a gain related to the strength of the torque (1020).

[0096] The wearable device (110) selects one of the motion types belonging to a determined interaction mode based on the user's (120) walking parameters (1030). The walking parameters may include several walking feature values ​​that represent the walking characteristics of the user (120). For example, the walking parameters may include the first and second walking feature values ​​described above.

[0097] The wearable device (110) determines a control factor for torque based on a selected motion type (1040). For example, the wearable device (110) can search for a control factor corresponding to the selected motion type in a lookup table. As another example, the wearable device (110) can determine a control factor corresponding to the selected motion type through a regression function or regression analysis. In an embodiment, the control factor for each motion type can be optimized through training.

[0098] The wearable device (110) generates torque (1050) based on processed state variables, gains, and determined control factors. Here, the processed state variables are as described above. y(t) It may correspond to. The wearable device (110) can generate torque by applying different control factors for each motion type. Accordingly, the linear response characteristics and control stability of the wearable device (110) can be improved.

[0099] Since the matters described through FIGS. 1 to 9 can be applied to the matters described through FIG. 10, a detailed description is omitted.

[0101] FIG. 11 is a block diagram illustrating a wearable device according to one embodiment.

[0102] Referring to FIG. 11, the wearable device (110) includes a controller (310) and an actuator (1110).

[0103] The controller (310) performs the overall operation of the wearable device (110) described through FIGS. 1 to 10. The controller (310) processes a defined state variable based on the movement information of the user (120) and determines the interaction mode of the wearable device (110) based on a gain related to the strength of the torque of the wearable device (110). Additionally, the controller (310) selects one of the motion types belonging to the determined interaction mode based on the walking parameters of the user (120) and determines a control factor for the torque based on the selected motion type. The controller (310) controls the actuator (1110) based on the processed state variable, the gain, and the determined control factor.

[0104] The actuator (1110) generates torque under the control of the controller (310).

[0105] As illustrated in FIG. 11, the wearable device (110) may include one actuator (1110), but as described through FIG. 2 and FIG. 3, the wearable device (110) may include a plurality of actuators (210-1 to 210-2).

[0106] Since the matters described through FIGS. 1 to 10 can be applied to the matters described through FIG. 11, a detailed description is omitted.

[0108] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0110] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0112] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

Claim 1 A method of operating a wearable device comprising: a step of measuring the angles of both hip joints of a user; a step of determining the user's motion type among motion types classified by movement speed based on the user's step information - said step information is based on the time taken or walking distance when the user takes a step -; and a step of controlling an actuator of the wearable device based on the measured angles of both hip joints, a gain related to the strength of the torque, and the value of the delay so that a torque related to the determined motion type is generated at a time delayed by the value of the delay related to the torque output timing of the wearable device. Claim 2 A method of operation of a wearable device according to claim 1, further comprising the step of determining the interaction mode of the wearable device through the gain. Claim 3 A method of operation of a wearable device according to claim 2, wherein the step of determining the interaction mode comprises, when the sign of the gain is a first sign, determining the interaction mode as a first interaction mode that assists the movement of the user, and when the sign of the gain is a second sign, determining the interaction mode as a second interaction mode that resists the movement of the user. Claim 4 A method of operation of a wearable device according to claim 1, wherein the step of determining the motion type comprises: a step of determining the user's cadence using the step information; a step of determining the motion type as a walk motion type when the cadence is less than or equal to a first threshold; a step of determining the motion type as a walk-to-run motion type when the cadence is greater than the first threshold and less than or equal to a second threshold; and a step of determining the motion type as a run motion type when the cadence is greater than the second threshold. Claim 5 A wearable device comprising: an actuator that generates torque; a sensor that measures the angles of both hip joints of a user; and a controller that controls the actuator based on the angles of both hip joints measured by the sensor, a gain related to the strength of the torque, and the value of the delay, such that the motion type of the user among motion types classified by movement speed is determined based on the user's step information, and torque related to the determined motion type is generated at a time delayed by the value of the delay related to the torque output timing of the wearable device, wherein the step information is based on the time taken or walking distance when the user takes a step. Claim 6 In paragraph 5, the wearable device, wherein the controller determines the interaction mode of the wearable device through the gain. Claim 7 A wearable device according to claim 6, wherein the controller determines the interaction mode as a first interaction mode that assists the user's movement when the sign of the gain is a first sign, and determines the interaction mode as a second interaction mode that resists the user's movement when the sign of the gain is a second sign. Claim 8 A wearable device according to claim 5, wherein the controller determines the user's cadence using the step information, and if the cadence is below a first threshold, determines the motion type as a walk motion type, if the cadence is greater than the first threshold and below a second threshold, determines the motion type as a walk-to-run motion type, and if the cadence is greater than the second threshold, determines the motion type as a run motion type.

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